Search Results for design of experiments

After the failure analysis team hypothesizes failure causes, prepares a failure mode assessment and assignment, and evaluates all potential failure causes, it may find in some cases that several causes are still suspect but cannot be confirmed. In this situation, an experiment is necessary to confirm or rule out suspected causes. This chapter discusses two predominant methods for doing this, namely analysis of variance (ANOVA) and Taguchi methods (a more powerful technique based on ANOVA).

This chapter discusses the extrusion technology of soft- and medium-strength aluminum alloys. The relative extrudability ratings of some soft- and medium-grade alloys are given. The chapter presents useful extrusion parameters and their relationships associated with day-to-day production practices in the aluminum extrusion industry. Useful parameters discussed include: extrusion runout; extrusion pressure; ram or extrusion speed control; and butt or extrusion discard thickness control. The chapter provides fundamental approaches to introducing and developing the design of experiments (DOE) for the aluminum extrusion plant to improve overall productivity. It also focuses on heat treatment of aluminum alloys.

At the conclusion of a systems failure analysis, the people involved should have a much more in-depth understanding of how the system is supposed to work. The analysis should help understand shortfalls in the design, production, testing, and use of the system. The failure analysis team will have identified other potential failure causes and actions required to preclude future failures. This is valuable knowledge, and it should not be set aside or ignored when the failure analysis team concludes its activities. This chapter is a brief account of the creation of failure analysis libraries, of process guidelines based on previous failure analyses, and of troubleshooting and repair guidelines. Also provided is a listing of the various steps that should be included in a failure analysis procedure.

Casting quality and consistency need to be carefully controlled. This chapter discusses the procedures that describe the process and product quality controls. In addition, it provides information on quality assurance programs.

This chapter provides an introduction to statistical process control and the concept of total quality management. It begins with a review of quality improvement efforts in the extrusion industry and the considerations involved in developing sampling plans and interpreting control charts. It then lays out the steps that would be followed in order to implement statistical testing for billet casting, die performance, or any other process or variable that impacts extrusion quality. The chapter concludes with an overview of the fundamentals of total quality management.

This chapter surveys both basic quality and basic reliability concepts as an introduction to the failure analysis professional. It begins with a section describing the distinction between quality and reliability and moves on to provide an overview of the concept of experiment design along with an example. The chapter then discusses the purposes of reliability engineering and introduces four basic statistical distribution functions useful in reliability engineering, namely normal, lognormal, exponential, and Weibull. It also provides information on three fundamental acceleration models used by reliability engineers: Arrhenius, Eyring, and power law models. The chapter concludes with information on failure rates and mechanisms and the two techniques for uncovering reliability issues, namely burn-in and outlier screening.

This chapter focuses on what can cause a system to fail and addresses the challenge in approaching a system failure. It then examines the steps involved in the four-step problem-solving process: defining the problem, identifying all potential failure causes and evaluating the likelihood of each, identifying the potential solutions, and identifying the best solution. The chapter concludes by describing the responsibilities of a failure analysis team.

This chapter presents two case studies; one demonstrating the use of finite-element analysis (FEA) in the design of a progressive die forming operation, the other explaining how software simulations helped engineers reduce thinning and eliminate cracking and deformation observed in clutch hubs formed using a three-step transfer die process. It also discusses the role of FEA and commercial software in the design of progressive dies.

In some cases, the failure analysis team finds that all components meet their requirements, the system was properly assembled, and it was not operated or tested in an out-of-specification manner, yet it still failed. When this occurs, the only conclusion the failure analysis team can reach is that it missed something in its analysis or that the design is defective. This chapter focuses on the latter possibility by discussing the various factors that a failure analysis team should consider to identify the causes of defects in system design. These include requirements identification and verification, circuit performance, mechanical failures, materials compatibility, and environmental factors. Examples that illustrate the value of design analysis are also presented.

Designs and materials continue to become more complex, with novel technologies developed to create them, and novel instruments invented to analyze them. Engineers at all stages of the design and manufacturing process should appreciate the reasons why formal failure analysis is performed. This chapter describes why failure analysis is conducted and outlines the responsibilities of the failure analyst.

The successful design and manufacture of gears are influenced largely by design requirements, material selection, and proper heat treatment. This chapter addresses the cost factors and tradeoffs involved in selecting a material, design features, and a heat treating process to optimize gear performance for a particular application.

This chapter provides guidelines on how to set up and run an effective quality-improvement program for aluminum extrusion operations. It begins by identifying production processes and variables that impact the quality of hard and soft alloy extrusions. It then presents a series of checklists and flowcharts that can be used to monitor and troubleshoot billet-making and extrusion processes, die construction, equipment maintenance, heat treating, and sawing and stretching procedures. It also discusses the importance of charting test results and monitoring surface treatments that may be required to improve corrosion, oxidation, or wear resistance.

This chapter presents guidelines for reducing gearbox vibration, with an emphasis on design factors that play major roles in influencing vibration.

This appendix contains drawings that illustrate the test specimens used in generating the data related to aluminum alloy castings.